The mechanical events of the heart are preceded and initiated by the electrochemical activity of the heart (i.e., the propagation of the action potential). In a healthy heart, the electrical and mechanical operation of the heart is regulated by electrical signals produced by the heart's sino-atrial (SA) node located in the right atrial wall. Each atrial depolarization signal produced by the SA node spreads across the atria, causing the depolarization and contraction of the atria, and arrives at the atrioventricular (A-V) node. The A-V node responds by propagating a ventricular depolarization signal through the “Bundle of His” of the ventricular septum and thereafter to the “Bundle Branches” and the Purkinje muscle fibers of the right and left ventricles. The signals propagated through the Bundle Branches effects depolarization and accompanying contraction of the left ventricle and the right ventricle in close order. Following contraction, the myocardial cells repolarize during a short period of time, returning to their resting state. The right and left atria refill with venous and oxygenated blood, respectively, until the cardiac cycle is again commenced by a signal originating from the SA node. At rest, the normal adult SA node produces an atrial depolarization signal approximately 60 to 85 times a minute, causing the heart muscle to contract, and thereby pumping blood to the remainder of the body. The electrical signal passes through the heart chambers as a wave front that can be characterized as a plane advancing from cell to cell through the cardiac muscle that separates cells of different electrical potential as a function of the time that it takes to complete the cardiac cycle.
The above-described cardiac cycle is disrupted in diseased or injured hearts, and the chronic or episodic disrupted electrical activity has long been employed to diagnose the state of the heart. A variety of techniques have been developed for collecting and interpreting data concerning the electrical activity of the heart using external medical devices (EMDs) both in the clinical setting and by way of portable external monitors worn by an ambulatory patient or implantable medical devices (IMDs) implanted in an ambulatory patient to collect data relating to electrical heart function during daily activities of the patient. Such techniques include electrocardiography, vectorcardiography and polarcardiography.
The cardiac cycle as displayed in an ECG lead tracing reflects the electrical wave front as measured across an ECG lead, that is between two spaced apart electrodes on the patient's body, as shown in U.S. Pat. No. 4,587,976, for example. The portion of a cardiac cycle representing atrial depolarization is referred to as a “P-wave.” Depolarization of the ventricular muscle fibers is represented by “Q”, “R”, and “S” points of a cardiac cycle. Collectively these “QRS” points are called an “R-wave” or a “QRS complex.” Re-polarization of the depolarized heart cells occurs after the termination of another positive deflection following the QRS complex known as the “T-wave.” The QRS complex is the most studied part of the cardiac cycle and is considered to be the most important for the prediction of health and survivability of a patient. However, the time relation of the P-wave to the QRS complex and the height and polarity of the T-wave and S-T segment are also indicators of a healthy or diseased heart. The S-T segment of a healthy heart is usually isoelectric, i.e., neither positive nor negative in deflection from baseline of the ECG lead tracing. This S-T segment is a most important indicator of the health of the ventricular myocardium and is elevated in ischemia and due to infarctions disrupting the depolarization wave front.
The beat rate of a normal heart is governed by the atrial depolarization rate, which is regulated by the body's current requirement for cardiac output reflecting a level of physical exercise or stress. The normal cardiac cycle and heart rate described above are disrupted in many instances. Conduction defects affecting the A-V node response to a P-wave can cause the ventricles to beat too slowly, that is exhibit bradycardia, and not provide sufficient cardiac output. Other conduction defects and/or disease processes can cause the atria and/or ventricles to spontaneously depolarize at a rapid rate, that is, to exhibit a tachyarrhythmia, that diminishes or disrupts cardiac output. Such ventricular tachyarrhythmias include ventricular tachycardia (VT) and ventricular fibrillation (VF).
In AF, the atria depolarize at an elevated rate that is often highly irregular, and the atrial depolarizations are typically conducted intermittently to the ventricles, so that the ventricles beat synchronously at times and asynchronously at other times with the atrial depolarizations. In AFL, the atria beat at an elevated rate that is highly regular, and a portion of the atrial depolarizations are typically conducted to the ventricles, whereby the ventricles often beat synchronously with every second or third atrial depolarization. Thus, the ventricular heart rate can be in a normal range or elevated but is often regular during an AFL episode, whereas the ventricular heart rate can be in a normal range or elevated but is usually irregular during an AF episode. Episodes of AF and AFL affect the atrial mechanical function and can have an effect on the ventricular heart rate that negatively affects cardiac output of the ventricles. These episodes can be accompanied by faintness, syncope, and tachyarrhythmia palpitation symptoms and can occur spontaneously and intermittently.
Moreover, at times, the atria prematurely contract due to depolarizations initiated at ectopic foci other than the SA Node in the atrium, referred to as Premature Atrial Contractions (PACs) or ectopic P-waves. These PACs can be conducted to the ventricles to result in a ventricular contraction or can, due to their amplitude, be mistakenly detected in the ventricles as an R-wave or a ventricular depolarization conducted from the AV node.
Similarly, the ventricles can also develop ectopic foci that intermittently cause a spontaneous depolarization wave front or Premature Ventricular Contractions (PVCs) or ectopic R-waves. Such PACs and PVCs and other arrhythmias can be visually identified by trained medical care providers in the PQRST segments displayed on ECG tracings, if they manifest in the clinical setting.
The ventricular heart rate is determined as a function of the interval between successive ventricular depolarizations each marked by the R-wave of the electrocardiogram (ECG) or electrogram (EGM), that is, the RR interval between successive detected R-waves. Generally, the time interval between successive R-waves is denoted as the RR interval, and the difference between successive RR intervals is denoted as the ΔRR interval or the dRR interval in the figures. A rapid and regular or irregular ventricular heart rate can be a normal sinus rhythm (NSR) tracking the normal atrial heart rate or can be due to PVCs and/or PACs or conducted AF or AFL or due to VT or VF originating in the ventricles.
There are many instances where it is desirable to be able to diagnose intermittent spontaneous cardiac arrhythmias, particularly AF and AFL, in ambulatory patients. There is a recognized need to improve the capability of detecting and distinguishing various types of atrial and ventricular tachyarrhythmias from NSR and one another
For many years, such patients, as well as patients suffering other bradyarrhythmias and tachyarrhythmias, have been equipped with external ECG monitoring systems, e.g., the patient-worn, real time Holter monitors, that continuously sample the ECG from skin electrodes and record it over a certain time period. Then, the ECG data must be analyzed to locate evidence of an arrhythmia episode and its nature and characteristics from which a diagnosis can be made.
As described in commonly assigned U.S. Pat. No. 5,312,446 and in U.S. Pat. No. 4,947,858, both incorporated herein by reference, the externally worn ECG recorders have inherent limitations in the memory capacity for storing sampled ECG and EGM data. Cost, size, power consumption, and the sheer volume of data over time have limited real time external Holter monitors to recording 24-hour or 48-hour segments or recording shorter segments.
The use of the externally worn Holter monitor coupled with skin electrodes is also inconvenient and uncomfortable to the patient. The skin electrodes can work loose over time and with movement by the patient, and the loose electrodes generates electrical noise that is recorded with the EGM signal and makes its subsequent analysis difficult. It has long been desired to provide an implantable monitor or recorder that is hardly noticeable by the patient and provides capabilities, such as recording ECG data correlated with an arrhythmia episode that is automatically detected or gathering statistics about a patient's clinical condition, such as the number of hours/day of arrhythmias the patient is experiencing.
Over the last 40 years, a great many IMDs have been clinically implanted in patients to treat cardiac arrhythmias and other disorders including implantable cardioverter/defibrillators (ICDs) and pacemakers having single or dual chamber pacing capabilities, cardiomyostimulators, ischemia treatment devices, and drug delivery devices. Recently developed implantable pacemakers and ICDs employ sophisticated atrial and/or ventricular tachyarrhythmia detection criteria based on heart rate, rate stability and onset and/or the morphology and other characteristics of the atrial and/or ventricular EGM. Most of these ICDs employ electrical leads bearing bipolar electrode pairs located adjacent to or in an atrial and/or ventricular heart chamber for sensing a near field EGM or having one of the electrodes located on the ICD housing for sensing a far field, unipolar EGM. In either case, the near field or far field EGM signals across the electrode pairs are filtered and amplified in sense amplifiers coupled thereto and then processed for recording the sampled EGM or for deriving atrial and/or ventricular sense event signals from P-waves and/or R-waves of the EGM.
The atrial sense event signals are typically generated by atrial sense amplifiers when the P-wave amplitude exceeds an atrial sense threshold. Similarly, the ventricular sense event signals are typically generated by ventricular sense amplifiers when the R-wave amplitude exceeds a ventricular sense threshold. The ventricular heart rate is typically derived from the measured RR interval between successive ventricular sense event signals.
In current ICDs providing a therapy for treating a cardiac arrhythmia, the sense event signals and certain aspects of the sampled EGM waveform are utilized to automatically detect a cardiac bradyarrhythmia or tachyarrhythmia in one or more heart chamber and to control the delivery of an appropriate therapy in accordance with detection and therapy delivery operating algorithms. In such cardiac ICDs providing pacing or cardioversion/defibrillation therapies, both analog and digital signal processing of the EGM is continuously carried out to sense the P-wave and/or R-wave events and to determine when a cardiac arrhythmia episode occurs. For example, a digital signal processing algorithm is employed to distinguish various atrial and ventricular tachyarrhythmias from one another. However, single chamber ICDs are more typically implanted to respond to single chamber tachyarrhythmias, and do not sense in both the atria and ventricles.
It is of great importance that such single chamber ventricular ICDs that are implanted to detect malignant ventricular tachyarrhythmia episodes, e.g. malignant VT or VF, accurately detect such VT and VF episodes to trigger delivery of the programmed ventricular anti-tachyarrhythmia therapy. An AF or AFL episode can so affect the apparent RR intervals that are being monitored as to satisfy the VT/NF detection criteria, triggering the delivery of an inappropriate and possibly dangerous VT/VF therapy. An inappropriately delivered VT/VF cardioversion/defibrillation shock therapy could induce a VT/NF episode rather than terminate the nonexistent VT/NF episode. Therefore, it is necessary to accurately discriminate between such atrial and ventricular tachyarrhythmias to avoid such occurrences.
When a tachyarrhythmia episode is detected in an ICD, at least selected EGM signal segments and sense event histogram data or the like are stored on a FIFO basis in internal RAM for telemetry out to an external programmer at a later time. Many of these ICDs are also capable of being operated to sample the EGM and transmit real time EGM data of indefinite length via uplink telemetry transmissions to the external programmer when a medical care provider initiates a real time telemetry session using the programmer.
Implantable cardiac monitors have also been developed and clinically implanted that employ the capability of recording cardiac EGM data for subsequent interrogation and uplink telemetry transmission to an external programmer for analysis by a physician. The recorded data is periodically uplink telemetry transmitted to a programmer operated by the medical care provider in an uplink telemetry transmission during a telemetry session initiated by a downlink telemetry transmission and receipt of an interrogation command.
The MEDTRONIC® Reveal™ insertable loop recorder is a form of implantable monitor that is intended to be implanted subcutaneously and has a pair of sense electrodes spaced apart on the device housing that are used to pick up the cardiac far field EGM which in this case is also characterized as a “subcutaneous ECG”. The Reveal™ insertable loop recorder samples and records one or more segment (depending on the programmed operating mode) of such far-field EGM or subcutaneous ECG signals when the patient feels the effects of an arrhythmic episode and activates the recording function by applying a magnet over the site of implantation. For example, the storage of a programmable length segment of the EGM can be initiated when the patient feels faint due to a bradycardia or tachycardia or feels the palpitations that accompany certain tachycardias. The memory capacity is limited, and so the segments of such EGM episode data that are stored in memory can be written over with new EGM episode data when the patient triggers storage and the memory is full. The most recently stored segment or segments of episode data is transmitted via an uplink telemetry transmission to an external programmer when a memory interrogation telemetry session is initiated by the physician or medical care provider using the programmer. Aspects of the Reveal™ insertable loop recorder are disclosed in commonly assigned PCT publication W098/02209 and in U.S. Pat. Nos. 5,987,352 and 6,230,059.
There are a variety of techniques known in the art for reducing raw data, e.g., recorded ECG or EGM data, to a more meaningful form. One such method is the statistical analysis to reduce the raw data to one or more statistical numbers representative of the raw data. Morphological techniques have been developed to compare sample ECG waveforms to waveform templates representative of NSR, and various arrhythmia templates. Various ways of categorizing heart rate in 1-D histograms, including the morphology of RR intervals collected from patients during known NSR and AF episodes have also been investigated in the effort to automate the detection of AF.
In, “A Method for Detection of Atrial Fibrillation Using RR Intervals”, by Tateno et al., published in Computers in Cardiology 2000, 27:391–394, the authors describe a method for automatic detection of atrial fibrillation (AF) based on comparison of density histograms of a number, e.g., 100, successive RR intervals and ΔRR intervals from a patient recording to a plurality of standard density histograms of a like number of either successive RR intervals or ΔRR intervals derived from a database and known to be representative of NSR or AF. The described method estimates the similarity between the standard density histograms and a test density histogram by the Kolmogorov-Smirnov (KS) test of the integral of the densities. The test density histogram is declared to evidence AF if it meets the KS test of not significantly different from the standard density histogram for AF.
Another technique used to reduce the data is to plot the data in some fashion that simplifies the interpretation of the data, e.g. as a Lorenz plot, which is a specific type of scatter plot. Such plots are a powerful graphic tool that can be applied to raw data to reduce the data to a form that can be more readily interpreted. There are various ways of identifying and selecting R-waves, processing the RR intervals and ΔRR intervals, displaying the Lorenz plots, and visually analyzing the Lorenz plots described in the prior art.
For example, such plotting process is described in U.S. Pat. No. 5,622,178, and in “Numeric Processing of Lorenz Plots of R-R Intervals From Long-term ECGs”, by Hnatkova et al., Journal of Electrocardiology, Vol. 28 Suppl. pp. 74–80, 1995. In a Lorenz plot, the two successive RR intervals defined by three successive R-waves are defined as a “first RR interval” and a “second RR interval” and plotted in the 2-D scatter-plot as a data point of the scatter-plot. The first RR interval is the time between the first and second R-waves of the set of three R-waves, and the second RR interval is the time between second and third R-waves of the set of three R-waves. The first RR interval is plotted on one of the abscissa and the ordinate, and the second RR interval is plotted on the other of the abscissa and the ordinate. Assuming, for example, that the first RR interval is plotted on the abscissa, then the second RR interval is plotted on the ordinate. The first data point is then plotted at the intersection of the measured abscissa and ordinate within the 2-D field of the scatter-plot.
When the next succeeding or fourth R-wave is detected, the set of three R-waves is redefined as comprising the second, third and fourth R-waves, and the RR interval is measured between the third R-wave and the fourth R-wave. The “first RR interval” then becomes the time between the second and third R-waves, and the “second RR interval” becomes the time between the third and fourth R-waves. Based upon the above assumption, the newly defined first RR interval is plotted on the ordinate, and the second RR interval is measured on the abscissa. The second data point is then plotted at the intersection of the measured abscissa and ordinate.
The process then continues with each detected R-wave of the set to be plotted. The order of plotting each of the newly defined first and second RR intervals on the abscissa or ordinate reverses each time. The process continues for a predetermined time segment or number of R-waves.
Successively measured ΔRR values can be plotted in the same manner as RR intervals in a Lorenz plot. FIGS. 1A–1D are illustrative Lorenz plots of two-minute segments of ΔRR values that exhibit distributions of plotted data points that are characteristic of episodes of AF (FIG. 1A), NSR (FIG. 1B), AFL (FIG. 1C), and PVCs and/or PACs (FIG. 1D).
Beat-to-beat variability measure is used to generate Lorenz plots of RR intervals of collected ECG data as described in “Patterns of beat-to-beat variability in advanced heart failure”, by Woo et al., American Heart Journal, Vol. 23, No. 3, pp. 704–710 (March, 1992).
Research has also been conducted to use such Lorenz scatter-plots of RR intervals from collected ECG data to illustrate episodes of AF affecting the RR intervals. See, for example, “Silent Zone on Lorenz Plots of the Ventricular Response Before Termination of Paroxysmal Atrial Fibrillation”, by Nakatsu et al., Japanese Circulation Journal, Vol. 58, pp. 676–682, August, 1994, which contains a case report showing that in the patient, a specific pattern could be identified near the termination of AF. See also, “The Mechanism of the Silent Zone on Lorenz Plots in Atrial Fibrillation”, Roczniki Akademij Medycznej Bialymstoku, by Pedich et al., Vol. 43, pp. 232–244, 1998, where it was demonstrated that the hypotheses in the case report by Nakatsu et al. was not valid when tested on more patients, i.e., the observed patterns did not correlate with the termination of AF. These references indicate how challenging the problem of determining AF can be. See also “Arrhythmia Analysis by Successive RR Plotting”, by Anan et al., Journal of Electrocardiology, Vol. 23, No. 3, pp. 243–248, July, 1990. Here it is stated that a wide scattering of points in an Lorenz plot was diagnostic of AF; however, no method of determining this other than visually is described.
In the above-referenced '178 patent, techniques are disclosed for selecting which RR intervals are the most appropriate to include in a scatter-plot to present scatter-plot data in a manner that permits flexibility in the selection of analysis and display parameters. Minimum and maximum RR intervals are specified bounding the RR intervals that are included in a given scatter-plot. Moreover, the source of the heartbeats, such as normal and ectopic heartbeats, that are included in a scatter-plot are specified by a beat source analyzer in the system disclosed in the '178 patent.
To the inventor's understanding, the prior art does not appear to teach or disclose a method or structure for atrial arrhythmia detection and/or characterization by identifying formations in a scatter plot derived from ventricular beats.
There remains a need for algorithms for characterizing, discriminating, and detecting atrial arrhythmias and other cardiac physiological conditions, from ventricular episodes, beat-to-beat.